Cista System Corp.

Zhaojian Li

Jiangtao Pang

Hirofumi Komori

Yang-Ting Chou

ChingJu Hsiao

Shenglong Yang

This application describes method and apparatus for LED Flickering Management (LFM) using spatially multiplexed image sensors. An example method includes configuring the sensor with diverse exposure settings to capture images of a scene with an LED light source. For each pixel position, multiple intensity values are collected across these images. An estimated linear regression model, incorporating an estimated Quantum Efficiency (QE) factor, is constructed using these values. The pixel intensities are then adjusted based on this estimated QE factor, aligning them with the regression model. This process results in modified images of the scene, effectively managing LED flickering for accurate image capture.

Light-emitting diode (LED) flickering management (LFM) for spatially multiplexed image sensor

Provided are an image sensor with one or more image receivers for image switching, and an imaging system and method therefor. The image sensor includes an image sensor array to generate first image data for a first image; a receiver to receive, into the image sensor, second image data for a second image; an image selection circuit coupled to the image sensor array and the receiver to receive the first image data and the second image data and select one of the first image data and the second image data according to one or more image selection criteria and at least one of the first image data and the second image data; and a transmitter coupled to the image selection circuit to transmit the selected one of the first image data and the second image data from the image sensor.

Image sensor with image receiver and automatic image switching

This application describes methods and systems for dark shading calibration and correction. An example method may include configuring an image sensor into a plurality of sensor states to capture a plurality of dark images, determining a dark current distribution on each of the plurality of dark images captured by the image sensor to obtain a plurality of dark current distributions respectively corresponding to the plurality of sensor states, storing the plurality of dark current distributions in a memory associated with the image sensor, capturing an image by the image sensor at a first sensor state, determining a first dark current distribution for the first sensor state of the image sensor based on the plurality of dark current distributions stored in the memory, and offsetting dark current noise on the image based on the first dark current distribution for the first sensor state of the image sensor.

Apparatus and method of dark current calibration and correction

This application describes method and apparatus for HDR+ using M×N-cell sensors. An example apparatus includes a plurality of pixel groups, each pixel group having M×N pixels configured with color filters of a same color such that the M×N pixels in each pixel group capture a same color. M and N are integers greater than one, and each pixel is represented by a first number of bits. The example apparatus further include one or more processors configured to: capture, through the plurality of pixel groups, a plurality of frames of a scene using a short-exposure setting; merge the plurality of frames into an HDR image; and perform tone mapping on the HDR image to reduce a dynamic range of the super-pixels of the HDR image into a low dynamic range (LDR) image, wherein each pixel in the LDR image is represented with the first number of bits.

HDR plus with MxN-cell image sensor

This application describes systems and methods for detecting depth in deep trench isolation with semiconductor devices using test key transistors. An method comprises: capturing, by an image sensor, an image; generating a plurality of chrominance channels by converting the image into luminance-chrominance space; performing homogeneous region segmentation on the plurality of chrominance channels to generate one or more regions of interest in the plurality of chrominance channels; and projecting the regions of interest onto eigen-illuminant images to determine gray color pixels on the image, wherein the eigen-illuminant images are generated via performing a machine learning algorithm on a training set of images captured by the image sensor.

Adaptive auto white balancing

Provided are an image sensor with one or more image receivers for image combining, and an imaging system and method therefor. The image sensor includes an image sensor array to generate first image data for a first image; a receiver to receive, into the image sensor, second image data for a second image; an image combination circuit coupled to the image sensor array and the receiver to receive the first image data and the second image data and combine the first image data and the second image data into combined image data for a single combined image, according to one or more image combination criteria, and at least one of the first image data and the second image data; and a transmitter coupled to the image combination circuit to transmit the combined image data for the combined image from the image sensor.

Image sensor with image receiver and automatic image combining

A high dynamic range sensing device is disclosed. The device includes an array of Bayer pattern units. Each of the Bayer pattern units comprises a plurality of pixels and each of the plurality of pixels comprises a plurality of photodiodes. At least one of the plurality of photodiodes in each pixel is configured to detect near infrared (NIR) light and at least one of the plurality of photodiodes in each of the plurality of pixels is configured to detect visible light.

Growing community of inventors

Fremont, CA, United States of America

Zhaojian Li